Interaction style describes the type of activities given to learners (e.g., step-based, exploratory). Domain and breath refer to the knowledge domain in which the work was situated (humanities, language learning, social sciences or STEM) and the number of topics and length of time the instruction covers. Type and focus refers to whether the paper describes an empirical study or not, and what are its main contributions for example, describing a system evaluation, a modeling approach, or a literature review. We analyse each paper along the following dimensions: type and focus of paper, domain and breath, interaction type and collaborative structure, technology used, learning setting, and learning goals. (i) What are the current foci of research in AIED? And, (ii) what changes do we need to undergo in order to lead education in the 21st century?
How can we build ILEs that enable high-quality adaptive education at scale? We address these questions by answering two related questions. Both students and teachers are in need of better, personalized support. However, many existing classroom structures are inapt for engaging students in “big” problems (Kirschner et al., 2006 Tobias & Duffy, 2009) or for offering students choice (Collins & Halverson, 2010). These transitions in education are also an opportunity: current educational theories advocate for more agency and personalization (Collins & Halverson, 2010). To maintain its relevance and increase its impact, the field of AIED has to adapt to these changes.
Subsequently, today’s educational environments and theories strive to incorporate authentic practices using big problems in collaborative settings. The introduction of 21st century skills (Trilling & Fadel, 2009) and Next Generation Science Standards (NGSS, 2013) have highlighted the importance of more general learning skills and competencies such as metacognition, critical thinking, and collaboration. However, this use-case fails to account for many recent developments in practices and theories of education. By making the human tutor our gold standard, a typical use-case has often been that of one student working with a computer in a math or science classroom to solve step-based problems focused on domain-level knowledge (cf.
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